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Efficient IoT data security using lattice-based multi-key homomorphic proxy re-encryption
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DOI：10.1186/s13677-026-00964-9.png)
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Abstract
En 中文
In today’s interconnected world, IoT devices have transformed daily life by automating processes and improving productivity. However, as these devices handle large volumes of sensitive data, robust security mechanisms are essential. Traditional encryption approaches face growing challenges with the advent of quantum computing, necessitating the development of quantum-resistant solutions. This study presents a future-proof approach for securing IoT data using multi-key homomorphic encryption, proxy re-encryption, and a lattice-based key-switching mechanism based on the Learning With Errors assumption. The proposed scheme is evaluated both theoretically and experimentally on a dataset of 1000 IoT devices. Under the chosen parameter settings, the scheme achieves a re-encryption time of approximately 140 ms, an encryption/decryption time of around 280 ms, and a key generation time of 80 ms. The results demonstrate that the proposed approach offers competitive performance in terms of key generation, encryption/decryption, and re-encryption time, while showing lower runtime compared to selected baseline schemes in our experimental setup.
Keywords:
Learning with errors
Anti-collusion
Homomorphic encryption
Key switching
Trapdoor sampling
Proxy re-encryption
Journal
J
IF:
4.3
Papers:
724
Citations:
2.2K